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Ordo Ab Chao

leveraging social media

sentiments

- 2 -

Corporate profile

Founded by IIT Madras alumnus having extensive global business experience with Fortune 100

companies in United States and India having three lines of business

Prof Prakash Sai

Dr. Prakash Sai is professor at the Department of Management Studies, Indian Institute of Technology Madras. He has wealth of international consulting experience in Strategy Formulation

Puneet Gupta

Puneet spearheads the IFMR Mezzanine Finance (Mezz Co.), is strengthening the delivery of financial services to rural households and urban poor by making investments in local financial institutions.

Padma Shri Dr. Ashok Jhunjhunwala

Dr. Ashok Jhunjhunwala is Professor at the Department of Electrical Engineering, Indian Institute of Technology Madras India. He holds a B.Tech degree from IIT, Kanpur, and M.S. and Ph.D degrees from the University of Maine, USA.

Analytics

• Appropriate statistical models

through which clients can measure

and grow their business.

Competitive Intelligence

• Actionable insights to clients for

their business excellence

Livelihood

•Services ranging from promotion of

livelihoods, implementation services,

livelihood & feasibility studies.

Key Focus Areas in Advanced analytics and Predictive analytics

Product – geniSIGHTS (Analytics/BI), Ordo-ab-Chao (Social Media)

More than 25 consulting assignments for Businesses & Govt orgs

Partnership – Actuate, IIT Madras, TIE and 3 strategic partnerships

Dedicated corporate office at IIT Madras Research park since 2009

Aaum’s office, IIT Madras Research Park

- 3 -

Competencies in

Advanced analytics

Build appropriate statistical models through

which clients can measure and grow their

business.

Expertise in

• Digital Media

• Finance/Insurance

• Retail

• Entertainment

• Human Capital

• Government organizations

• Research & training

Competitive

assessment

Competitive intelligence

Provide actionable insights to clients for

their business excellence.

Expertise in

•Business Entry

•Business Expansion

•Market research

Livelihood

Perform livelihood services ranging from

promotion of livelihoods, implementation

services, livelihood and feasibility studies.

Expertise in

•Government organizations

•Non Government

organizations

•Corporate with livelihood

focus

•Research

- 4 -

Problem Description Current Process

Market Segments

Size of Addressable Market

Only about half of the businesses using social

media networks like Facebook, Twitter, or

LinkedIn have any idea as to a return on

investment.

Businesses doesn’t know how to leverage

the insights effectively for their operations.

Sound understanding of business objectives will

be helpful to devise appropriate methodologies

to extract/analyze information from web.

Many players existing to categorize sentiments

based on text mining techniques but no solution

existing on predicting social media based

on advanced analytics real time to benefit

the business goals.

Articulating the current scenario in social media

Th

e P

ro

ble

m

Most of the businesses have presence in web, get

feedback to gather from comments and derive

insights manually or by leveraging software (just

classification) available in the market.

All business segments – No differentiation

Assuming 40% of the companies have presence

in the web. And 50 % of them have adopted

social media or using social media techniques.

This is a very captive market looking at the

impact made by social media in the recent years.

- 5 -

Solution Description Proposed Process

Market Segments

Size of Addressable Market

Aaum have developed a working concept to

predict/categorize social media comments by

various business parameters.

Customized advanced analytical algorithms,

dictionary have been developed to accomplish

this.

This product has potential to change the

business paradigm.

With continuous data mining and right infrastructure,

it is now possible to know people’s choice specific to

the business.

Just the tip of the iceberg and Sky is the limit!

Please refer to the proof of concept in the next

slide.

Aaum’s solution envisioned

Ou

r S

olu

tion

Automatic sentiment mining from social media.

Predict social media opinions real time based on

advanced analytics to benefit the business

objectives.

All business segments – No differentiation

Assuming 40% of the companies have presence

in the web. And 50 % of them have adopted

social media or using social media techniques.

This is a very captive market looking at the

impact made by social media in the recent years.

Business objectives

• Generate more word of mouth

• Increase customer loyalty

• Bring outside ideas into organization

• Increase product/brand awareness

• Improve new product success ratios

• Improve public relations effectiveness

• Reduce customer acquisition costs

• Reduce customer support costs

• Reduce market research costs

• Reduce product development costs

Prioritized business

• Generate more word of mouth <2

• Increase customer loyalty <4

• Bring outside ideas into organization <3

• Increase product/brand awareness <5

• Improve new product success ratios

• Improve public relations effectiveness <1

• Reduce customer acquisition costs

• Reduce customer support costs

• Reduce market research costs

• Reduce product development costs

- 6 -

Problem Description Competitive comparison

Competitive positioning by key factors

Social media is sunrise industry.

Many software companies are making tools to

come up with solutions to categorize the

comments based on basic text mining

techniques

None of these tools have good predictive

solutions for the business to derive insights

for their operations.

Aaum’s solution is a blue ocean product to

leverage the benefits of analytics in social

media.

Competitive landscape

Co

mp

etitio

n

A few commercially available packages

SAS, SPSS

– Performs text mining and categorizes by key words

– Adopts a generic approach

Customized solutions (Many vendors)

Based on dictionary classification and partially on

advanced analytics

Visibli, Semioboard, viralheat, etc

– More of web analytics

A comprehensive solution with continuous monitoring

is lacking in this space!

Differentiators Aaum’s solution Competition

Text mining and automatic comments extraction

Partial

Prediction by business parameters

Partial

Prediction by advanced analytical techniques and therefore better prediction/accuracy

Continuous mining of data and hence not limited to one time “api” search

Case Study: Comparative Sentiment Analysis on Pongal release movie “What people expressed before the

release & post the release”

Case S

tud

y

- 8 -

Data collected from various sources based on the business rules

formed....

- 9 -

Removing the bias factor is a very important process in our approach in addition to

other data cleansing activities and transformation techniques

Username

No. of

tweets

AllAboutVijay 209

rahulsundar_007 197

AllAbtVijay 150

TheVijay360 143

VijayAnban 141

Actor_Vijay 127

techboss2011 126

j_shanujan 119

DineshSelvakuma 110

abhi_vfrndz89 106

VijayExpress 104

tamizhanlogesh 97

MelanieWF 96

Vijay_theactor 95

cinemausher 76

rohith_vijayfan 74

VIJAY_FansClub 73

may_war 71

cineandhra 61

IIAYATHALABATHY 59

Username

No. of

tweets

Dhananjayang 93

Star_falilah 84

techboss2011 51

yuvanfansclub 50

meyyappanram 45

prakash_12345 44

TamilStudios 42

crajapriyan 40

ActorMadhavan 40

amala_amsfc 39

Thus_S 30

Magenraja 29

Actor_Amalapaul 29

97thstreetswgrx 29

vigneshwar_m 27

LatchmiGirl 27

j_shanujan 27

sruthii4u 26

TweetSav 24

rajg_kumar 24

‘Nanban’ ‘Vettai’

- 10 -

Key insights

Did the movie meet the expectations of the crowd

– Pre-release vs Post release

How did the movie perform?

– 7 days before vs 7 days after

Key Enabling factors

Key Deteriorating factors

Scope for improvement

– Preventive and corrective actions

See all by yourself in our Movie-meter dashboard!!!

– Prediction based on our training algorithms

- 11 -

0

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Movie Hero Heroine Direc tor S ong Movie Hero Heroine Direc tor S ong

Nanban Vettai

Neutral Negative Pos itive

0

2000

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12000

Movie Hero Heroine Direc tor S ong Movie Hero Heroine Direc tor S ong

Nanban Vettai

Neutral Negative Pos itive

0

1000

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Movie Hero Heroine Direc tor S ong Movie Hero Heroine Direc tor S ong

Nanban Vettai

Neutral Negative Pos itive

0

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8000

10000

12000

14000

Movie Hero Heroine Direc tor S ong Movie Hero Heroine Direc tor S ong

Nanban Vettai

Neutral Negative Pos itive

With out bias

With out bias With bias

With bias

Post release

Pre release

Our classification techniques are based on advanced analytical algorithms

- 12 -

Insights from our analysis

Pre release analysis shows a very good support for both the movies.

A very few negative criticisms

Heavy promotions witnessed in case of Vettai

Removal of bias factors provides an altogether different perspective!

Post release analysis also shows a very good support for both the movies.

Nanban as clearly emerged a ‘victor’

More positive comments about the movie, direction and the hero

And nobody cares for songs from any of the movies!!!

- 13 -

Possible applications

“Ordo Ab Chao” - our analytical product, a powerful listening tool to

mine social media sentiments

– Local movies chosen to initiate buzz and to create viral marketing

The product demonstrated finds wide application areas especially

– FMCG companies – To understand the customer behavior and usage

patterns.

• Effectiveness of campaign launch, advertisements

– Company, Competition and Customer

• e.g. New brand launch

– Social media companies/Communities – to cater their services effectively to

their customers.

• e.g. Twitter?

– Entertainment industry - To understand the customer sentiments.

• Academy awards, News channels, etc

- 14 -

Want to see trends, changing audience perspectives on the movie

attributes?

vs

Take a dive into the next slides

- 15 -

Nanban –Insights for movie and hero

Hero

-50

0

50

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12/18/2011 12/23/2011 12/28/2011 1/2/2012 1/7/2012 1/12/2012 1/17/2012 1/22/2012

Negative Neutral Positive

Hero

0 0 0 0 0 0 0 0

1

0 01

05 4 0

5 1 4 17 26 17 3 16 14 1

1 1 1

2

8 4 6

1

1

6 413

7

129 120

12

83

76

58

262268

269 186

221294

62

0 0 0

1

0 0 0

1

0 0 0 0 0

36 38

0

40

8

50

307284

158 102

203220

52

0%

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80%

100%

12/2

1/2

011

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Negative Neutral Positive

Movie-Nanban

0 0 0 0

1

0 0 0 0 0

11 13 9 0 11 9 23 96 116 132 54 74 56 13

2

1 1 1 3 3 2

1

4

11

1268

497 61227

837 356 458

15622042

174170811431245342

1

0 0 0

1

0 0

1

1

0 0 0

83 912

11564

105

704705

424 177360 348 81

0%

20%

40%

60%

80%

100%

12/2

0/2

011

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/2012

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012

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012

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012

Negative Neutral Positive

Movie-Nanban

-500

0

500

1000

1500

2000

2500

12/18/2011 12/23/2011 12/28/2011 1/2/2012 1/7/2012 1/12/2012 1/17/2012 1/22/2012

Negative Neutral Positive

Pre & Post release insights

- 16 -

Director -Nanban

1

0

4 2

0

1

0 0 0

1

0

1713

4

28

11

35

120

225

85

53

8169

21

0

0

0 0

0

0

0 0 0

0

0

01

0

5

0

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5

8

20

6

6

4

1

0

0

0 0

0

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0 0 0

0

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0 0 0

18

4

4

170

7946

19

5035

1

0%

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12/2

6/2

011

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011

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011

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/2012

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012

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Neutral Negative Positive

Heroine -Nanban

8 1 7

8

4

8 9

16

30

14

9

42

216

0 0 0

0

0

0 0

10

12

0 2

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00 0 0

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1 1

10

84

2 7

10

0%

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/2012

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/2012

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012

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012

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012

Neutral Negative Positive

Heroine-Nanban

0

5

10

15

20

25

30

35

40

45

50

1/3/2012 1/6/2012 1/9/2012 1/12/2012 1/15/2012 1/18/2012 1/21/2012

Negative Neutral Positive

Director-Nanban

0

50

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300

12/22/2011 12/25/2011 12/28/2011 12/31/2011 1/3/2012 1/6/2012 1/9/2012 1/12/2012 1/15/2012 1/18/2012 1/21/2012

Neutral Negative Positive

Nanban –Insights for director and heroine

Pre & Post release insights

- 17 -

Questions/Feedback?

Contact us

01 N, 1st floor IIT Madras Research Park, Kanagam road, Chennai – 600113

Tel :` +91 44 66469877, Fax:+91 44 66469877

Email: info@aaumanalytics.com, Skype:b.rajeshkumar

Twitter: AaumAnalytics, Web: www.aaumanalytics.com

Facebook: http://www.facebook.com/AaumAnalytics

LinkedIn: http://www.linkedin.com/company/aaum-research-and-analytics-iit-madras

About Aaum

Aaum Research and Analytics founded by IIT Madras alumnus brings in extensive global business

experience working with Fortune 100 companies in North America and Asia Pacific. Incubated at IIT

Madras Incubator ecosystem with a focus on researching and devising the sophisticated analytical

techniques to solve the pressing business needs of corporations ranging from Health Care,

Entertainment, FMCGs, finance, insurance, retail, Telecom.

Aaum’s office at IIT Madras Research Park